Daytum exists to train coding experts in oil and gas. Getty Images

Nearly 2,000 miles separate the energy industry of Houston and Silicon Valley where startups have cropped up to help manage the thousands of data points collected on oil rigs each day. The different geographies have developed their own dialects: data scientists on the West Coast talk about how operations should be, according to their models, while the lingo of Third Coast engineers and technicians centers on oil-specific operations.

Last year, while working in natural resource investing from Houston, Kunal Rayakar realized he had heard from a number of students who could, uniquely, speak both. The reason: They knew coding languages, which meant they could analyze their own data and bridge that gap between the coasts. When Rayakar followed the trail of students to the University of Texas at Austin, he found two engineering professors, John Foster and Michael Pyrcz, who were teaching their students data skills as part of the curriculum. They started talking, and eventually Foster and Rayakar founded daytum — and soon after, Pyrcz joined, too.

"The intention is to give people more awareness of the data that comes through, so they can make faster decisions," Rayakar says.

An education program for workers in the energy industry, daytum hosts workshops and an online learning network for technicians and engineers to better understand the data they're working with. This, Rayakar says, helps them exercise more control over the work — especially for those whose preliminary training in the field was before data became indispensable to the job. The professors and Kunal host two– or five-day workshops, and just a few weeks ago, they held both introductory and intermediate courses at the University of Houston.

The professors teach Python, a common programming language. Although there's a learning curve to studying Python, it's not as confusing as some of the tools, like MATLAB, that engineers studied in their undergraduate educations. But students don't actually have to become Python experts at all — instead, they use Jupyter, an online digital notebook that can import Python packages, which are large and ready-made coding sequences.

Often, these are free and available to download on sites like Github. Daytum professors teach packages that are useful for analyzing and visualizing the data they work with in the field, and students leave having a usable workstation on their computers, ready to be installed and implemented in their work.

"People really enjoyed the courses," Rayakar says. "We were really happy."

But right now, daytum's main goal is to continue to grow its workshops — including introducing Austin bootcamps, to engage people in learning, and to empower oil industry technicians to navigate the industry's digital transition more smoothly.

"By building longer-term solutions and cultures, we can build better educations," Rayakar says.

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How Houston innovators played a role in the historic Artemis II splashdown

safe landing

Research from Rice University played a critical role in the safe return of U.S. astronauts aboard NASA’s Artemis II mission this month.

Rice mechanical engineer Tayfun E. Tezduyar and longtime collaborator Kenji Takizawa developed a key computational parachute fluid-structure interaction (FSI) analysis system that proved vital in NASA’s Orion capsule’s descent into the Pacific Ocean. The FSI system, originally developed in 2013 alongside NASA Johnson Space Center, was critical in Orion’s three-parachute design, which slowed the capsule as it returned to Earth, according to Rice.

The model helped ensure that the parachute design was large enough to slow the capsule for a safe landing while also being stable enough to prevent the capsule from oscillating as it descended.

“You cannot separate the aerodynamics from the structural dynamics,” Tezduyar said in a news release. “They influence each other continuously and even more so for large spacecraft parachutes, so the analysis must capture that interaction in a robustly coupled way.”

The end result was a final parachute system, refined through NASA drop tests and Rice’s computational FSI analysis, that eliminated fluctuations and produced a stable descent profile.

Apart from the dynamic challenges in design, modeling Orion’s parachutes also required solving complex equations that considered airflow and fabric deformation and accounted for features like ringsail canopy construction and aerodynamic interactions among multiple parachutes in a cluster.

“Essentially, my entire group was dedicated to that work, because I considered it a national priority,” Tezduyar added in the release. “Kenji and I were personally involved in every computer simulation. Some of the best graduate students and research associates I met in my career worked on the project, creating unique, first-of-its-kind parachute computer simulations, one after the other.”

Current Intuitive Machines engineer Mario Romero also worked on Orion during his time at NASA. From 2018 to 2021, Romero was a member of the Orion Crew Capsule Recovery Team, which focused on creating likely scenarios that crewmembers could encounter in Orion.

The team trained in NASA’s 6.2-million-gallon pool, using wave machines to replicate a range of sea conditions. They also simulated worst-case scenarios by cutting the lights, blasting high-powered fans and tipping a mock capsule to mimic distress situations. In some drills, mock crew members were treated as “injured,” requiring the team to practice safe, controlled egress procedures.

“It’s hard to find the appropriate descriptors that can fully encapsulate the feeling of getting to witness all the work we, and everyone else, did being put into action,” Romero tells InnovationMap. “I loved seeing the reactions of everyone, but especially of the Houston communities—that brought me a real sense of gratitude and joy.”

Intuitive Machines was also selected to support the Artemis II mission using its Space Data Network and ground station infrastructure. The company monitored radio signals sent from the Orion spacecraft and used Doppler measurements to help determine the spacecraft's precise position and speed.

Tim Crain, Chief Technology Officer at Intuitive Machines, wrote about the experience last week.

"I specialized in orbital mechanics and deep space navigation in graduate school,” Crain shared. “But seeing the theory behind tracking spacecraft come to life as they thread through planetary gravity fields on ultra-precise trajectories still seems like magic."

UH breakthrough moves superconductivity closer to real-world use

Energy Breakthrough

University of Houston researchers have set a new benchmark in the field of superconductivity.

Researchers from the UH physics department and the Texas Center for Superconductivity (TcSUH) have broken the transition temperature record for superconductivity at ambient pressure. The accomplishment could lead to more efficient ways to generate, transmit and store energy, which researchers believe could improve power grids, medical technologies and energy systems by enabling electricity to flow without resistance, according to a release from UH.

To break the record, UH researchers achieved a transition temperature 151 Kelvin, which is the highest ever recorded at ambient pressure since the discovery of superconductivity in 1911.

The transition temperature represents the point just before a material becomes superconducting, where electricity can flow through it without resistance. Scientists have been working for decades to push transition temperature closer to room temperature, which would make superconducting technologies more practical and affordable.

Currently, most superconductors must be cooled to extremely low temperatures, making them more expensive and difficult to operate.

UH physicists Ching-Wu Chu and Liangzi Deng published the research in the Proceedings of the National Academy of Sciences earlier this month. It was funded by Intellectual Ventures and the state of Texas via TcSUH and other foundations. Chu, founding director and chief scientist at TcSUH, previously made the breakthrough discovery that the material YBCO reaches superconductivity at minus 93 K in 1987. This helped begin a global competition to develop high-temperature superconductors.

“Transmitting electricity in the grid loses about 8% of the electricity,” Chu, who’s also a professor of physics at UH and the paper’s senior author, said in a news release. “If we conserve that energy, that’s billions of dollars of savings and it also saves us lots of effort and reduces environmental impacts.”

Chu and his team used a technique known as pressure quenching, which has been adapted from techniques used to create diamonds. With pressure quenching, researchers first apply intense pressure to the material to enhance its superconducting properties and raise its transition temperature.

Next, researchers are targeting ambient-pressure, room-temperature superconductivity of around 300 K. In a companion PNAS paper, Chu and Deng point to pressure quenching as a promising approach to help bridge the gap between current results and that goal.

“Room-temperature superconductivity has been seen as a ‘holy grail’ by scientists for over a century,” Rohit Prasankumar, director of superconductivity research at Intellectual Ventures, said in the release. “The UH team’s result shows that this goal is closer than ever before. However, the distance between the new record set in this study and room temperature is still about 140 C. Closing this gap will require concerted, intentional efforts by the broader scientific community, including materials scientists, chemists, and engineers, as well as physicists.”

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This article originally appeared on EnergyCapitalHTX.com.